A minimal nontrivial example of higher-order evidence

被引：0

作者：

Cole, Stephen R. ^{[1
]}

Shook-Sa, Bonnie E. ^{[2
]}

Zivich, Paul N. ^{[1
]}

Edwards, Jessie K. ^{[1
]}

机构：

[1] Univ North Carolina, Gillings Sch Global Publ Hlth, Dept Epidemiol, Chapel Hill, NC USA

[2] Univ North Carolina, Gillings Sch Global Publ Hlth, Dept Biostat, Chapel Hill, NC USA

来源：

AMERICAN JOURNAL OF EPIDEMIOLOGY | 2025年

关键词：

bias; measurement error; random error; systematic error;

D O I：

10.1093/aje/kwae321

中图分类号：

R1 [预防医学、卫生学];

学科分类号：

1004 ; 120402 ;

摘要：

Higher-order evidence (ie, evidence about evidence) allows epidemiologists and other health data scientists to account for measurement error in validation data. Here, to illustrate the use of higher-order evidence, we provide a minimal nontrivial example of estimating the proportion and show how higher-order evidence can be used to construct sensitivity analyses. The proposed method provides a flexible approach to account for multiple levels of distortion in the results of epidemiologic studies.

引用

页码：886 / 888

页数：3

共 38 条

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